1 Technical Field
Embodiments of the subject matter disclosed herein generally relate to methods and systems and, more particularly, to mechanisms and techniques for determining a main axis of symmetry for an anisotropic velocity model.
2 Discussion of the Background
During the past years, the interest in developing new oil and gas production fields has dramatically increased. However, the drilling is an expensive process. Thus, those undertaking the drilling need to know where to drill in order to avoid a dry well.
Seismic data acquisition and processing generate a profile (image) of the geophysical structure under the seafloor or subsoil. While this profile does not provide an accurate location for the oil and gas, it suggests, to those trained in the field, the presence or absence of oil and/or gas. Thus, providing a high resolution image of the structures under the seafloor/subsoil is an ongoing process.
To construct images of the subsoil (or subsurface), geologists or geophysicists conventionally use wave emitters (sources) placed on the surface, for example. For the case of marine seismic, the wave emitters are towed by a vessel at or under the surface of the water. Such emitters emit waves which propagate through the subsoil (and water for the marine seismic) and which are reflected on the surfaces of the various layers thereof (reflectors). Waves reflected to the surface are recorded as a function of time by receivers (which are towed by the same vessel or another vessel for the marine seismic or lay on ocean bottom). The signals received by the receivers are known as seismic traces.
It is conventional to pick portions of such seismic traces which correspond to reflections of pulses emitted from the surface, and which correspond to reflectors of interest, and also to determine the travel times that correspond to such reflections. Tomography inversion techniques consist in modeling velocity fields within the subsoil as a function of the acquired seismic traces and of selected events.
Tomography is commonly used in depth imaging of seismic data for estimating wave propagation velocity (P-waves, S-waves) and anisotropic parameters (epsilon, delta, sigma, see for example, Thomsen, L. A., 1986, Weak elastic anisotropy, Geophysiscs, Vol. 51, No. 10, October, P. 1954-1966, the entire content of which is incorporated herein by reference). The tomography can be ray-based or wave equation-based, it can invert surface seismic data or Vertical Seismic Profile (VSP) (also called borehole seismics) data, it can estimate one or more velocity parameters.
In conventional imaging processing, the main direction of anisotropy of the subsurface is often assumed to be equal to the structural dip that follows the geology of the subsurface; when referring to transverse isotropy, this case is often referred to as Structural Transverse Isotropy (STI). In this regard, FIG. 1 shows a portion of the subsoil 10 having various layers 12, 14, 16. The tilt axis 18 for a portion 20 of the layer 12 is perpendicular (for most cases) to the surface of the portion 20. The tilt axis is picked from a seismic migrated cube usually obtained by depth migration in an isotropic or Vertical Transverse Isotropy (VTI) or STI or Tilted Transverse Isotropy (TTI) model. The picked tilt axis is usually inserted into the velocity model to describe its main symmetry axis. This will affect wave propagation in this velocity model. The post-stack or pre-stack depth migration of seismic data in the updated model produces a new migrated seismic image, slightly different from the original seismic image. Thus, the tilt axis model does not match any longer a re-migrated structure. Existing techniques are unable to produce a tilt axis model that matches the migrated image, except by re-iterating several times a loop shown in FIG. 2. FIG. 2 shows such a loop that starts at step 30 with a migration model. Based on this model, the seismic data is migrated in step 32 and in step 34 a dip is picked. In step 36 a STI tilt is computed and in step 38 the migration model is updated based on this data. This process (loop) illustrated in FIG. 2 is computer intensive as the migration and dip picking are repeatedly calculated. Further, this process may not fully converge.
TTI velocity is commonly considered nowadays in seismic depth imaging. STI is the most popular instantiation of TTI velocity where the tilt axis follows the geological structures. In all that follows, STI-related tilt axis means a tilt axis that can be computed partly from a structural (geological) dip, where the dip is a line perpendicular to a facet of the geological structure. In a typical situation, the geophysicist picks STI-related axis on migrated images created by migrating seismic data in an anisotropic model that contains an initial guess for the STI axis. To obtain a more precise image, the geophysicist then integrates the picked STI-related tilt axis into the anisotropic velocity model and re-migrates the seismic data because the modified anisotropy model impacts the wave propagation and thus, the migration/positioning of the migrated seismic data. This process can be repeated several times to obtain a satisfactory anisotropic velocity model as illustrated in FIG. 2. However, as noted above, this process is computer intensive, as the migration and dip picking have to be performed each time the model is updated.
Accordingly, it would be desirable to provide systems and methods that avoid the afore-described problems and drawbacks.